ID | 69061 |
フルテキストURL | |
著者 |
Fortmeier, Vera
Department of General and Interventional Cardiology, Heart and Diabetes Center Northrhine-Westfalia, Ruhr University Bochum
Hesse, Amelie
Department of Internal Medicine I, Klinikum rechts der Isar, TUM University Hospital, School of Medicine and Health, Technical University of Munich
Trenkwalder, Teresa
DZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance
Tokodi, Márton
Heart and Vascular Center, Semmelweis University
Kovács, Attila
Heart and Vascular Center, Semmelweis University
Rippen, Elena
Department of Internal Medicine I, Klinikum rechts der Isar, TUM University Hospital, School of Medicine and Health, Technical University of Munich
Tervooren, Jule
Department of Internal Medicine I, Klinikum rechts der Isar, TUM University Hospital, School of Medicine and Health, Technical University of Munich
Fett, Michelle
Department of General and Interventional Cardiology, Heart and Diabetes Center Northrhine-Westfalia, Ruhr University Bochum
Harmsen, Gerhard
Department of Physics, University of Johannesburg
Yuasa, Shinsuke
Department of Cardiovascular Medicine, Okayama University
Kühlein, Moritz
Department of Cardiovascular Diseases, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich
Covarrubias, Héctor Alfonso Alvarez
Department of Cardiovascular Diseases, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich
von Scheidt, Moritz
DZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance
Roski, Ferdinand
Department of Cardiovascular Diseases, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich
Gerçek, Muhammed
Department of General and Interventional Cardiology, Heart and Diabetes Center Northrhine-Westfalia, Ruhr University Bochum
Schuster, Tibor
Department of Family Medicine, McGill University
Mayr, N. Patrick
Institute of Anesthesiology, German Heart Center Munich, School of Medicine and Health, TUM University Hospital, Technical University of Munich
Xhepa, Erion
DZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance
Laugwitz, Karl‐Ludwig
Department of Internal Medicine I, Klinikum rechts der Isar, TUM University Hospital, School of Medicine and Health, Technical University of Munich
Joner, Michael
DZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance
Rudolph, Volker
Department of General and Interventional Cardiology, Heart and Diabetes Center Northrhine-Westfalia, Ruhr University Bochum
Lachmann, Mark
Department of Internal Medicine I, Klinikum rechts der Isar, TUM University Hospital, School of Medicine and Health, Technical University of Munich
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抄録 | Aims Long-standing severe mitral regurgitation (MR) leads to left atrial (LA) enlargement, elevated pulmonary artery pressures, and ultimately right heart failure. While mitral valve transcatheter edge-to-edge repair (M-TEER) alleviates left-sided volume overload, its impact on right ventricular (RV) recovery is unclear. This study aims to use both conventional echocardiography and artificial intelligence to assess the recovery of RV function in patients undergoing M-TEER for severe MR.
Methods and results The change in RV function from baseline to 3-month follow-up was analysed in a dual-centre registry of patients undergoing M-TEER for severe MR. RV function was conventionally assessed by measuring the tricuspid annular plane systolic excursion (TAPSE). Additionally, RV function was evaluated using a deep learning model that predicts RV ejection fraction (RVEF) based on two-dimensional apical four-chamber view echocardiographic videos. Among the 851 patients who underwent M-TEER, the 1-year survival rate was 86.8%. M-TEER resulted in a significant reduction in both LA volume and estimated systolic pulmonary artery pressure (sPAP) levels (median LA volume: from 123 ml [interquartile range, IQR 92–169 ml] to 104 ml [IQR 78–142 ml], p < 0.001; median sPAP: from 46 mmHg [IQR 35–58 mmHg] to 41 mmHg [IQR 32–54 mmHg], p = 0.036). In contrast, TAPSE remained unchanged (median: from 17 mm [IQR 14–21 mm] to 18 mm [IQR 15–21 mm], p = 0.603). The deep learning model confirmed this finding, showing no significant change in predicted RVEF after M-TEER (median: from 43.1% [IQR 39.1–47.4%] to 43.2% [IQR 39.2–47.2%], p = 0.475). Conclusions While M-TEER improves left-sided haemodynamics, it does not lead to significant RV function recovery, as confirmed by both conventional echocardiography and artificial intelligence. This finding underscores the importance of treating patients before irreversible right heart damage occurs. |
キーワード | Echocardiography
Mitral regurgitation
Right ventricular dysfunction
Deep learning
Transcatheter edge-to-edge repair
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発行日 | 2025-06-09
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出版物タイトル |
European Journal of Heart Failure
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出版者 | Wiley
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ISSN | 1388-9842
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NCID | AA11560829
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資料タイプ |
学術雑誌論文
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言語 |
英語
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OAI-PMH Set |
岡山大学
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著作権者 | © 2025 The Author(s).
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論文のバージョン | publisher
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PubMed ID | |
DOI | |
Web of Science KeyUT | |
関連URL | isVersionOf https://doi.org/10.1002/ejhf.3705
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ライセンス | http://creativecommons.org/licenses/by/4.0/
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Citation | Fortmeier, V., Hesse, A., Trenkwalder, T., Tokodi, M., Kovács, A., Rippen, E., Tervooren, J., Fett, M., Harmsen, G., Yuasa, S., Kühlein, M., Covarrubias, H.A.A., von Scheidt, M., Roski, F., Gerçek, M., Schuster, T., Mayr, N.P., Xhepa, E., Laugwitz, K.-L., Joner, M., Rudolph, V. and Lachmann, M. (2025), Employment of artificial intelligence for an unbiased evaluation regarding the recovery of right ventricular function after mitral valve transcatheter edge-to-edge repair. Eur J Heart Fail. https://doi.org/10.1002/ejhf.3705
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助成情報 |
( Technical University of Munich )
( Else Kröner-Fresenius Foundation )
( German Center for Cardiovascular Research )
( German Heart Foundation )
( Ruhr University Bochum )
( German Cardiac Society )
RRF-2.3.1-21-2022-00004:
( European Union )
TKP2021-NVA-12:
( Ministry of Culture and Innovation of Hungary )
( Hungarian Academy of Sciences )
( National Research, Development, and Innovation Office (NKFIH) of Hungary )
( Else Kröner-Fresenius Foundation )
( German Heart Foundation )
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